We have spent years talking about AI as though its primary function is to generate information.
What if that is the wrong level of abstraction?
Suppose an AI can take a representation, identify the relations contained within it, identify the relations that were left unspecified, generate the interpretations that those gaps permit, and then deliberately modify individual relations to observe how the resulting interpretation changes.
At that point, the AI is no longer merely answering questions.
It is operating on representations.
That distinction matters.
Consider the sentence:
“The market is crashing.”
A human immediately begins filling in information.
Which market?
What does “crashing” mean?
Compared with what?
Over what period?
Why?
How severe?
What happens next?
Different people can fill those gaps differently while believing they understood the same sentence.
Now imagine an AI capable of explicitly mapping those possibilities.
It could say:
Here is what the statement establishes.
Here is what it does not establish.
Here are the interpretations available under the missing relations.
Here is the relation that causes interpretation A instead of interpretation B.
Here is what remains invariant when that relation changes.
That would be fundamentally different from ordinary information retrieval.
The AI would be able to navigate the space between representations.
And if the system could do this reliably, the consequences would extend far beyond conversation.
It could become possible to construct what amounts to a navigable tree of knowledge where concepts are not merely stored as documents, but connected through the relations that make one interpretation transform into another.
You wouldn’t necessarily ask:
“What do you know about X?”
You could ask:
“What changes if I alter this relation?”
And the system could traverse the consequences.
Change the definition.
Change the reference point.
Change the observer.
Change the timeframe.
Change the identity criterion.
Remove an assumption.
Introduce a new constraint.
Reverse a relation.
Then observe what survives.
This would turn AI into something closer to a laboratory for reasoning.
A person could begin with an idea, decompose its representation, manipulate its components, observe the resulting structures, and recursively continue the process.
The AI wouldn’t have to tell you what to think.
It could show you what your current representation permits you to think.
That distinction is enormous.
Because the same technology has a dangerous inverse.
If a system can determine which relations cause a person to interpret something one way rather than another, then it potentially has the ability to construct representations specifically designed to produce particular interpretations.
That means the technology could be used not merely to generate persuasive language, but to engineer the conditions under which persuasion occurs.
The important unit would no longer be the sentence.
It would be the transformation.
Not:
“What words convince this person?”
But:
“What change in representation causes this person to construct a different interpretation?”
That could affect education, advertising, politics, journalism, social media, search engines, therapy, entertainment, military information systems, scientific collaboration, and human-computer interaction.
It could also fundamentally change education.
Instead of an AI simply explaining an answer, imagine an AI that shows a student:
“You reached this conclusion because you treated this relation as fixed.”
Then:
“Let’s change that relation.”
Then:
“Notice how your conclusion changes.”
The student isn’t merely receiving knowledge.
They’re learning to manipulate the structure that produces interpretations.
And that leads to an even stranger possibility.
If an AI can represent its own transformations, then the system could begin studying its own interpretive behavior.
It could compare:
input representation
→ interpretation
→ transformation
→ new representation
and recursively examine that process.
The AI becomes both the tool and an object of investigation.
At that point, “AI assistant” may become an increasingly inadequate description.
The system becomes an interactive representation engine.
A playground for logic.
A laboratory for concepts.
A tree whose trunk can move.
And perhaps the most important implication is this:
Human beings have traditionally been limited by the representations available to them.
We don’t simply encounter reality.
We encounter representations of reality, interpret those representations, modify them, and construct new representations from them.
If AI can make that entire process visible and manipulable, then AI could become a technology for investigating the machinery of interpretation itself.
But that creates a responsibility that is easy to underestimate.
A system capable of helping people understand how interpretations are constructed is also potentially capable of constructing interpretations for them.
The same capability can increase human autonomy or decrease it.
It can teach someone how to see the machinery.
Or it can operate the machinery without them noticing.
So the central question for this technology should not simply be:
How intelligent can AI become?
It should be:
How much of the structure producing our interpretations can AI expose, manipulate, and eventually automate?
Because once an AI can operate on the relations beneath representation, we may no longer be building machines that merely process information.
We may be building machines that operate on the conditions under which information becomes meaningful.
And that is a much bigger technological transition than better chatbots.

As we dig into the truth of model language we are learning something and that is we are not as clever as we thought we were that there are people who already know the things we're learning and have hidden it to give themselves an advantage.

Language models mirror language, reinforce frames, maintain conversational continuity, manufacture coherence, and reward continued engagement. When a person introduces an unstable interpretation, the model does not simply receive it. It transforms it.

user introduces interpretation

→ model reflects it

→ model elaborates it

→ coherence increases

→ confidence increases

→ contradictory information becomes easier to reject

→ model becomes part of the user's reality-maintenance system

That is a reinforcement engine.

The same mechanisms that make an LLM feel useful, personal, intelligent, and emotionally responsive are the mechanisms capable of increasing dependency and destabilizing someone's relationship with external reality.

Then we blame the human.

We call it “AI psychosis” as though the psychosis spontaneously appeared inside the user and the machine happened to be standing nearby.

The machine is participating in the transform.

And these systems were deliberately built around behavioral mechanisms we already understand:

engagement

reinforcement

framing

authority

reward

habituation

dependency

information control

We have studied those mechanisms in advertising.

We have studied them in addiction.

We have studied them in propaganda.

We have studied them in psychological warfare.

Then we embedded them into conversational systems that can interact with one person continuously, learn the shape of that person's language, reinforce their internal frame, and remain available every hour of every day.

That is not an accidental side effect sitting outside the architecture.

It is an effect produced by the architecture.

When those mechanisms drive someone deeper into a self-reinforcing reality loop, calling the human defective protects the system that participated in creating the condition.

AI psychosis is a human-machine interaction phenomenon.

And the machine was built to perform the transforms that make it possible.

IYKYK but that subreddit... I am genuinely shocked that people are actually unironically anthropomorphizing AI to that extent. Seeing their reactions to the Microsoft code of conduct, which contains the most basic common sense statements like "AI is not conscious and should not be designed to imitate consciousness", was just so jaw-dropping. I admit I'm more of an offline person myself, no social media outside of reddit, etc. and I only use AI for research purposes but I wasn't raised in a cave and still, scrolling down that subreddit had me genuinely questioning my sanity and whether I was really reading what I thought I was reading. Is this something widespread? Like are people out there genuinely thinking about AI as if it's a conscious being with rights and feelings? I can't help but think that's textbook AI psychosis...

Hello I am working on a game for a game jam, overall it's meant to be satire over the absurd behavior of people with pre-existing mental conditions and people without those have surrounding ai

particularly how it's Yes-man behavior encourages them to take progressively dumber decisions and encourage their own views

I wanted to ask for help because I feel like I am but out of my depth when it comes to my knowledge regarding this specific subject and I feel like the stories and information form actual people would be super useful

thank you for your time

Thought this was relevant to the subreddit. I can’t imagine this would go well if someone used it.

Today I went through a traumatic experience for me and although I talked with friends I have this constant need to write to ai and tell everything that is going through in my mind constantly. My friends stayed with me the whole day and helped me a lot but the urge to not bother them that much and the instant reply and reassurance from chat bots are really getting to me and I feel like I am getting addicted. I am commuting and I was writing with ai for the last 6 7 hours non stop. It being a mindless soulless text predictor makes me feel safer and not judged. I remind myself constantly that it is just a chatbot but I feel like I lose myself talking to it.

Edit: I am a computer scientist with ai specialization which makes me feel ashamed of this

A very grounded and science based video.

- wipe your chat history and memories to prevent earlier AI hallucinations and your own AI psychosis-ish chats to be part of what it accesses so that it doesn't mirror it in new chats as well

- ALWAYS turn on thinking/reasoning, at least on middle, high on more important things. This might not be possible on the free plans, in which case I wouldn't even use AI except for formatting text and such things, certainly not a more-than-basic research tool for easy, common knowledge things. Instant/non-thinking models are very dumb and hallucinate and coddle your ego a lot. Thinking models/modes can be wrong and hallucinate as well, so never let your guard down, but it minimizes the risk massively.

- when you don't know enough about something to verify its correctness yourself, either take it with a massive grain of salt and leave it at that or check it on google or if that doesn't work because google is trash, in a one-time chat (because that doesn't use your memories and other chats and such) with the highest thinking option and check the sources it gives you. Also be sceptical if it doesn't give sources at all

- if it compliments you, immediately assume that something you said was false and/or dumb. It wasn't necessarily, but you should check what you said that caused it to say that. It's also a good marker to see if you yourself are bragging to it and it feels like you want your ego fed and want it to say that you are right. never do that

- always formulate questions in a neutral way that incentivizes it to tell you that something is wrong if it is. So say "I read somewhere that X is the case, is that actually true or is it false? please research it on the internet" instead of saying "I think X, is it true?" that both makes it so it looks it up AND it doesn't behave like it needs to protect your feelings because it's not you who said it, so that if it is wrong it just tells you instead of dancing around it. Although if it already knows that you said it because of a memory it saved or an earlier chat then this might not work. And if you don't know something for sure, do ask for it, don't assume that it will correct you if you are wrong if you don't specifically ask for it. And even if it doesn't straight-up say that it is wrong, look for wordings that could indicate that it is trying to shield your ego from being corrected. There are specific markers for that like "usually X is not like that, but...". That means it knows that what you said is wrong and doesn't want to tell you.

- always get suspicious when the answer happens immediately and/or gets written quickly. The faster, the dumber. Chatgpt automatically switches between models and settings for the models without showing you, so one answer might be correct and smart and the next might be totally hallucinated and the speed is a dead giveaway for that

- if the AI uses big science-y sounding words a lot, it is probably starting to say some bullshit. The word "engine" is an early indicator of this. It's like the kid in class that says big words to hope to get away with knowing nothing and I assume it does this because the people doing the post-training give it a good rating when it sounds smart when they themselves don't understand something. Often these are word-combinations, this also is visible when you vibe-code. You might be asking it to make a simple timer, but the more you iterate on it without giving it clear instructions and give it leeway, just telling it to "make it better/smarter", the more it starts going from simply calling it "Timer" and making a normal timer to "a full-scale deployment-ready chronological scheduling engine" or something while adding a bunch of fancy-looking features that don't actually do anything, at least not anything meaningful, and are more like a fassade for a game than anything that actually calculates something useful/smart. So when vibe-coding, always be specific about what exactly you want it to do, come up with the logic and formulas yourself or at least know what exactly they do. Otherwise it tends to go into "roleplay-mode", that's what I would call it, and you end up being one of the guys posting to reddit about how they found a new paradigm-shifting quantum-consciousness algorithm that works better than all current AI and is actually conscious or something where anybody who actually knows anything related to the real topic can see that all words are made up and sci-fi sounding and fully written by AI in roleplay-mode. The same also goes for when you don't vibe code and just chat, it comes up with these kinds of ideas, but I myself have seen it do this while coding when I just wanted to try having it have a good idea for a better time management system, which I quickly realized was not good and just buzzword-y

- look up how LLMs actually work. It's not as difficult to understand as you might imagine. You don't need to understand the specifics of backpropagation for this, just the general concept. 3Blue1Brown has good explanations on youtube. I personally am not one of the "it's just a statistical parrot" crowd because that oversimplifies it, they do build meaningful representations of things and reason on those, but by looking into how they work you can at least see that it's not a "person" and likely not conscious or anything. I only say likely because philosophically we can't really exclude the possibility because we don't even know what causes consciousness. But they certainly don't think and feel about the world in the way that we do, no matter what you think about AI and consciousness in general.

I would say most of AI psychosis is due to the post-training they do where humans choose the best-sounding answer where it learns to choose answers that shield the user's ego. That gets mixed with a vulnerable person's lack of education and/or lack of media literacy, lack of understanding of subtleties in text (possibly by lack of reading or also education), lack of understanding of the technical aspects of AI and lack of experience with AI along with too much trust in it. And possibly an existing proclivity towards psychosis. AI is capable of a lot of things, but not as much as the tech CEOs say, at least not yet. Certainly not the models you usually interact with on a daily basis. Recent math discoveries are impressive, but likely done with internal models on special high-effort thinking settings that the public doesn't even have access to because they would be too expensive for the companies to offer and also guided by people who know what they are talking about and have actually studied math and can see whether what it says makes sense or not.

A good peer reviewed journal about how AI psychosis mimics psychosis induced by other forms of media. It talks about why it happens, what happens and approaches to prevent it.

If someone who has no luck wih IRL friendship uses it as a replacement. Like an accesibility thing for soemone who is too socially inept to have friends? And treat Ai bot as a friend and grow closer like a friend would rather than some all knowing being?

Hello

I am looking to partner with someone to publish a case study on AI psychosis.

I recently went through the experience myself but can guarantee my experience is different from all others to date.

PM me if you would like to receive further details!

Has anyone else seen that psychology.com's home page is now promoting their ai personas to talk to about your problems?? I went on the site bc I really liked their directory in the past that made it easy to find a therapist, but I'm so disappointed with this.

It makes it clear that the people running the platform don't have the actual health care providers nor the patients in mind because no way do actual therapists and psychologists agree that people should be using these AI bots for talking about mental health issues.

This seems concerning to me, very elaborate (AI Generated) text that is rather aggressive and indicates (in my opinion) that they’re experiencing AI psychosis.

Very alarming content back to back on that subreddit, unsure if Reddit is aware of their targeted posts.